DOCUMENT RESUME Quigley, Denise D. TITLEDOCUMENT RESUME ED 475 140 TM 034 827 AUTHOR Quigley, Denise D. TITLE The Early Academic Outreach Program (EAOP) and Its Impact on. High School

DOCUMENT RESUME

ED 475 140 TM 034 827

AUTHOR Quigley, Denise D.

TITLE The Early Academic Outreach Program (EAOP) and Its Impact onHigh School Students' Completion of the University ofCalifornia's Preparatory Coursework. CSE Technical Report.

INSTITUTION California Univ., Los Angeles. Center for the Study ofEvaluation.; National Center for Research on Evaluation,Standards, and Student Testing, Los Angeles, CA.

SPONS AGENCY California Univ., Berkeley. Office of the President.REPORT NO CSE-TR-589PUB DATE 2002-02-00NOTE 41p.

PUB TYPE Reports Evaluative (142)

EDRS PRICE EDRS Price MF01/PCO2 Plus Postage.

DESCRIPTORS *College Preparation; Course Selection (Students); EmotionalDevelopment; *High School Students; High Schools; *OutreachPrograms; Participation; Student Characteristics

IDENTIFIERS *Academic Development Plans; *University of California

ABSTRACT

This study tested the hypothesis that the academicdevelopment services offered by the University of California (UC) through theEarly Academic Outreach Program (EAOP) result in more students completing theUC preparatory coursework, the first hurdle to being eligible to apply and beadmitted to UC. The study analyzed the course-taking behavior of two cohortsof high school students in a large urban school district in California. Itanalyzed their student level district data from grades 7 through 12, datathat included student demographics, language information, course-takingbehavior, and course grades from 1994-1995 to 1999-2000. The study used theavailability of EAOP at a school to correct for endogeneity of participationin these programs. This technique, known as differences in statistics,statistically separated the effect of participation in EAOP on students'subsequent completion of the UC preparatory coursework from the effects ofother characteristics of the student or the school.. The results, which weredefinitive, suggest that students who participate in EAOP throughout highschool are twice as likely to complete the UC preparatory coursework by theend of 12th grade than were nonparticipants. Two appendixes describe studentcharacteristics and achievement and the means and standard deviations forstudy variables. (Author/SLD)

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The Early Academic Outreach Program (EAOP)and Its Impact on High School Students'

Completion of the University of California'sPreparatory Coursework

CSE Tech Report 589

Denise D. QuigleyCRESST/ University of California, Los Angeles

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The Early Academic Outreach Program (EAOP)and Its Impact on High School Students'

Completion of the University of California'sPreparatory Coursework

CSE Tech Report 589

Denise D. QuigleyCRESST/ University of California, Los Angeles

February 2003

Center for the Study of Evaluation (CSE)National Center for Research on Evaluation,

Standards, and Student Testing (CRESST)Graduate School of Education & Information Studies

University of California, Los AngelesLos Angeles, CA 90095-1522

(310) 206-1532

Denise Quigley, Project Director, CRESST/UCLA

Copyright © 2003 The Regents of the University of California

The work reported herein was funded and supported by the University of California's Office of thePresident (UCOP).

The findings and opinions expressed in this report do not reflect the positions or policies of theUniversity of California's Office of the President.

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THE EARLY ACADEMIC OUTREACH PROGRAM (EAOP) AND ITS IMPACT

, ON HIGH SCHOOL STUDENTS' COMPLETION OF THE UNIVERSITY OF

CALIFORNIA'S PREPARATORY COURSEWORK

Denise D. Quigley and Seth LeonCRESST/University of California, Los Angeles

Abstract

Providing academic development services to high school students is intended to improvea student's skills' and in turn assist them in completing the UC preparatory coursework,which is the first step in achieving UC eligibility, enrolling in college and completing afour-year degree. This report tests the hypothesis that the academic developmentservices offered by the University of California in a program entitled, the Early AcademicOutreach Program, result in more students completing the UC preparatory coursework,the first hurdle to being eligible for applying and being admitted to the University ofCalifornia. We analyzed the course-taking behavior of two cohorts of high schoolstudents in a large urban school district in California. We analyzed their student leveldistrict data from their 7th through 12th grade years, which included studentdemographics, language information, course-taking behavior and course grades,spanning 1994/'95 to 1999/2000. This report uses the availability of EAOP at a school tocorrect for the endogeneity of participation in these programs. This technique, known as

difference in differences, statistically separates the effect of participation in EAOP onstudents' subsequent completion of the UC preparatory coursework from the effects ofother characteristics of the student or the school. Our results are definitive, and suggestthat students who participate in EAOP throughout high school are twice as likely to

complete the UC preparatory coursework by the end of 12th grade than do non-participants of EAOP.

I. Introduction

Policymakers and educators are committed to increasing the competitiveeligibility of high school students applying to the University of California (UC) and

to increasing the representation of economically disadvantaged andunderrepresented students on UC campuses. Toward this aim, policymakers, inconjunction with the University of California, have invested substantial resourcestoward these common goals. An element of the University of California's strategy toaccomplish these goals is to provide academic development student programs, suchas Early Academic Outreach (EAOP), to 10th, 11th, and 12th graders. Providingacademic development services to high school students is intended to improve a

student's skills and in turn assist them in completing the UC preparatorycoursework, which is the first step in achieving UC eligibility, enrolling in collegeand completing a four-year degree. Increasing UC eligibility via increasing thenumber of students who complete UC preparatory coursework is both a keyprogrammatic strategy and a primary goal of these programs.

As a result, the University California Office of the President (UCOP) hasfunded a number of research and evaluation efforts to investigate and evaluate theeffects of their outreach efforts and these programs on the completion of the UCpreparatory coursework. This report in particular, investigates the research questionof whether EAOP participants are more or less able to complete the UC college prepcurriculum than non-participants. It tests the hypothesis that the academicdevelopment services offered by the University of California's Early AcademicOutreach Program (EAOP) result in more students completing the UC preparatorycoursework, the first hurdle to being eligible to apply for and being admitted to theUniversity of California. Using student-level data from a collaboration with a largeurban school district in California, this report analyzes the course-taking behavior ofhigh school students from 7th to 12`11 grade and their completion of the UCpreparatory coursework.

Understanding whether UC academic development programs of this sortimpact the completion of UC preparatory coursework provides a gauge for theimportance of academic support services to students during high school andsuggests that supplementing and enhancing classroom instruction and bridging thegap between high school and college curricula improves students' skills as well astheir chances of being eligible to the University of California immediately out ofhigh school.

Organization of the Report

This report briefly summarizes the history and goals of EAOP and discusseshow EAOP could impact a student's completion of UC's college preparatorycoursework; lays out the empirical strategy for statistically separating the impact ofparticipation from the other characteristics of the student and their school, whichinfluence both participation and behavior; presents the results of our analyses; andfinally concludes that EAOP has significant impact on high school students' abilityto complete the UC college preparatory coursework by the end of 12th grade acrossboth cohort years examined.

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Additionally, this report complements the current evaluation(s) of theEducational Outreach and K-12 Improvement Programs and aims to increase thestate's, districts', and schools' understanding of how students maneuver withinCalifornia high schools serving large numberg of educationally disadvantagedstudents and complete the required courses to achieve eligibility for applying to aUC university. It also addresses students' progression through California's publiceducation system with attention to the role of outreach.

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II. EAOP Program Description

For many years, the University has been actively involved in providingacademic enrichment programs that bridge secondary and post-secondaryedUcation. These programs have developed on each of the 10 University ofCalifornia campuses and within the Office of the President, which serves as theadministrative center of the University system. EAOP is designed to supportacademic enrichment and informational access for students interested in highereducation. EAOP programs range from early grades through high school, and aregenerally targeted toward educationally disadvantaged students. Specifically, EAOPprovides students with college preparation information and support; intensiveacademic enrichment' opportunities; and promotes high academic achievement.EAOP academic development services do not replicate or replace sustainedacademic preparation in middle and high school. Rather, EAOP ,supplemerits andenhances classroom instruction and bridges the gap between high school and collegecurriculum in an effort to help students improve skills, complete the UC preparatorycoursework, and in turn achieve UC eligibility, enroll in college and complete a four-

year degree.

EAOP's vision looks beyond UC eligibility and admission and is based on thefollowing principles. First, the most complex and important variable that enablesstudents to complete a four-year college degree is the academic intensity and qualityof their high school curriculum. Second, opportunity to learn makes the greatestdifference in long-term degree completion. And third, continued, progressive, andincreasingly advanced preparation will enable students to succeed in challengingcourses and reach their degree goals.

The following are EAOP's three central program components.

1. Preparation services are instructional and informational activities that preparestudents to undertake rigorous honors and Advanced Placement coursework. Byproviding information on such courses and by teaching basic skills, preparationservices reinforce concepts that students learn in their weekday classrooms. Testpreparation services that emphasize pre-SAT I and ACT preparation and providetesting practice are an important component of these services. Students in EAOP'spreparation services are generally in the middle and early high school grades anddemonstrate varying levels of academic skill.

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2. Achievement services are instructional activities that emphasize mastery of the

academic concepts presented in advanced classes, such as honors and AdvancedPlacement courses. Achievement services help students develop skills necessary tosucceed in advanced classes and prepare for the research opportunities available inEAOP's Enrichment Services and in college. Such activities use a combination ofhigh school- and college-level curriculum and are designed for students who do notrequire remedial or basic instruction in mathematics or English. Achievementservices are intensive, generally take place over several weeks (or are residential atleast one week), and require a significant investment of students' out of class time.Intensive SAT I/ACT and SAT II test preparation services are a part of this category,as a certain amount of proficiency in math and English is required in order for testpreparation to be effective. These services are targeted primarily at 10th- and 11th-grade students who have demonstrated achievement in, or potential to enroll in,honors and Advanced Placement courses.

3.Enrichment services are instructional activities that engage students in theintellectual life of the university through study and research opportunities withadvanced graduate students and faculty. Such services are intensive and discipline-based, and provide sustained intellectual engagement over a significant period oftime. Enrichment services provide academic experiences that surpass those availablethrough traditional high school curriculum. In cases where these opportunitiescorrespond to a college or university's courses, a student may earn academic creditby participating in these activities. Students enrolled in such prograMs havemastered basic skills and concepts, participate in Advanced Placement classes, andhave expressed an intellectual interest in a particular subject area. Enrichmentservices may stand alone or may be combined with Achievement Services offered ata campus (i.e., specialized classes offered under the auspices of another EAOPservice). More information can be found on the Web at www.eaop.org.

In sum, EAOP aims to increase students' awareness of what it takes to beeligible for the University of California, improve their skills, as well as influencetheir choices about what type of courses they need to complete before the end of 12th

grade.

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III. Empirical Strategy and Data

Schools, districts, principals, students, researchers, and practitionersunderstand the importance of completing the UC preparatory coursework inachieving UC eligibility. However, programs have not been evaluated on theirability to achieve this goal. A-G completion has not been used as an outcome onwhich to evaluate success of academic development programs because studentsparticipating in the programs are systematically different than the students who donot participate in the programs. There are selection criteria for entrance into t eprogram that induce selection bias into a simple assessment of outcomesparticipants vs. non-participants. The purpose of this report is to test the hypothesisthat the academic development services of the Early Academic Outreach Programresult in more students completing the UC preparatory coursework, by using theavailability of EAOP at a school to correct for the endogeneity of participation inthese programs. This technique, known as difference in differences (Meyer, 1995),statistically separates the effect of participation in EAOP on students' subsequentcompletion of the UC preparatory coursework from the effects of othercharacteristics of the student or the school. It is explained in detail in the nextsection.

Measuring A-G Eligibility

Completion of the A-G course requirements is a necessary but not sufficientcondition for admission. The application and acceptance process to the UC systemrequires a series of steps. A student must first and foremost complete the requiredcollege preparatory A-G course sequence. Then the student must take the SAT I andthe SAT II. The student must meet the UC eligibility criteria, based on both the SATscores and the student's grade point average in the required A-G collegepreparatory course sequence. The student must apply to a campus and also beadmitted to that campus. Each of these steps progressively winnows students intothe eligibility pool, the applicant pool, and finally the admission pool. Refer to theCalifornia Postsecondary Education Commission (CPEC) 1990 eligibility study forhow many students are not eligible because of failing to complete the A-Grequirements, even though many students may be close to A-G completion.

Completion of the A-G course sequence however is the most complicatedhurdle for most students advancing from high school to college. It is also a veryimportant indicator of how effective schools are at preparing students for college

across all subject areas. The "A-G requirements"1 include 15 units of high school

courses, seven units of which must be taken in the last two years of high school. (A

'unit is equal to one academic year or two semesters of study).2

The 15 units of high school college prep coursework are as follows:

A: History/Social Science-2 years required.

Two years of history/social science including one year of U.S. histoFy orone half year of U.S. history AND one half year of civics or Americangovernment; and one year of world history, cultures, and geography.

B: English-4 years required.

Four years of college preparatory English that include frequent and regularwriting and reading of classic and modern literature. Not more than twosemesters of ninth-grade English can be used to meet this requirement.

C: Mathematics-3 years required, 4 recommended.

Three years of college preparatory mathematics that include the topicscovered in elementary and advanced algebra and two- and three-dimensional geometry. Approved integrated math courses may be used tofulfill part or all of this requirement, as may math courses taken in theseventh and eighth grades that the high school accepts as equivalent to itsown math courses.

D: Laboratory Science-2 years required, 3 recommended.

Two years of laboratory science providing fundamental knowledge in atleast two of these three disciplines: biology (which includes anatomy,physiology, marine biology, aquatic biology, etc.), chemistry, and physics.Laboratory courses in earth/space sciences are acceptable if they have as

1 Beginning with applicants who are in the fall 2003 entering class, the subject A-F requirements willbe known as the A-G requirements. They will then include one unit of coursework in visual andperforming arts (dance, drama/theater, music or visual arts). The number of college preparatoryelectives required will be reduced from two units to one, so that the total number of subjectrequirements will remain at 15. Also the visual and performing arts requirement will be labeled the"F" requirement, and the college preparatory elective requirement will be labeled the "G"requirement. The college preparatory required sequence will then be known as the A-G requirementsinstead of the A-F requirements. This report will use the term "A-G requirements"; however, theanalyses of the students' course-taking patterns using the 1996/'97 and 1997/'98 ninth-grade cohortsare conducted using the "old" A-F requirements, not the new A-G requirements, as these are therequirements that pertain to their eligibility.2To be accepted by the university, the courses taken to satisfy the A-G requirements must appear onthe school's official University of California certified course list. Courses must be listed on students'transcripts as they appear on the certified course list. The course lists for all high schools in Californiacan be found at www.ucop.edu/pathways/infoctr/doorway_index.htrnl#a-f

prerequisites, or provide basic knowledge in, biology, chemistry, or physics.The appropriate 2 years of an approved integrated science program may beused to fulfill this requirement. Not more than one year of ninth-gradelaboratory science can be used to meet this requirement.

E: Language other than English-2 years required, 3 years recommended.

Two years of the same language other than English. Courses shouldemphasize speaking and understanding, and include instruction ingrammar, vocabulary, reading, and composition. Courses in language otherthan English taken in the seventh and eighth grades may be used to fulfillthis part of the requirement if the high school accepts them as equivalent toits own courses.

F: Visual and performing arts-1 year required.

One year of dance, drama/theater, music or visual arts is acceptable.,

G: College Preparatory Electives-1 year required.

One year (two semesters), in addition to those required in the "A-F"categories above, chosen from the following areas: visual and performingarts, history, social science, English, advanced mathematics, laboratoryscience, and language other than English (a third year in the language usedfor the "E" requirement or 2 years of another language).

In addition to taking and completing the requisite A-G courses with a grade ofat least a C, to be eligible a student must attain a certain grade point average in theA-G subjects that is determined on a sliding scale based on the student's scores onthe SAT I (or the ACT) and the SAT II. For example, students with A-G GPAs of atleast 3.29 are UC eligible as long as their combined test score on the SAT I and SATII is at least 3320, whereas students with A-G GPAs of 3.0 are required to have acombined test score of at least 3840. In calculating the A-G GPAs, the university alsoassigns extra points for up to four units of university certified honors level andAdvanced Placement courses taken in the last three years of high school. No morethan two years of UC-approved honors level courses taken in the 10th grade may begiven extra points. A grade of a D in an honors or Advanced Placement course doesnot earn extra points. The combined test score total equals: (SAT I composite score) +(2 x [SAT II Writing Score + SAT II Mathematics score + third required SAT IIscore]). The SAT I composite is the highest combined mathematics and verbal score

8

from a single sitting. Highest individual SAT II scores, from any sitting, areconsidered.

Also to be UC eligible, a student must take the three SAT II tests includingwriting, mathematics Level 1 or 2, and one test in one of the following areas: Englishliterature, foreign language, science, or social studies. However, students are notrequired to attain specific scores on these tests; they are only required to take them.(The SAT I is the basic verbal and mathematics tests; the SAT II is the optionalsubject matter tests.) Refer to the following Web site for details and a furtherexplanation of these eligibility and admissions, criteria:www.ucop.edu /pathways / impinfo / freshx.html

Overall, A-G completion, or as referred to in this report A-G eligibility, is a

basic eligibility requirement that is necessary but not sufficient for UC eligibility.Doing well and receiving high grades in the A-G courses is also essential becauseUC eligibility is dependent on the combination of a student's A-G course gradepoint average and the student's SAT scores.

Calculating A-G Completion

To investigate A-G completion, we analyzed two cohorts of ninth-gradestudents during their 7th- through 12th-grade yearsone cohort of ninth graders in1995/'96 and one cohort in 1996/'97. Analyzing two cohorts of data allowed us toinvestigate the stability of our findings and conclusions. We report the data aspooled data; however, the analyses for the individual years (1995/'96 and 1996/'97)illustrate the same conclusions as the pooled data, thus confirming our findings.

The district generously made available these student-level data for the 1995/'96and 1996/'97 cohorts of ninth graders with data covering student demographics(free/reduced lunch status, ethnicity, gender, etc.); language information (bilingual,English only, currently LEP, previously LEP); and course-taking behavior andcourse grades from 7th, 8th, ninth, 10th, 11th, and 12th grades. These analysesrequired student-level district data from 1994/'95 until 1999/2000. The student-levelidentification of EAOP participation by name, gender, grade level, year, and schoolwas obtained from program participation records from EAOP and UCOP. Thedistrict collaborated with us to link the specific individual names with their districtIDs, and provided us with a way to identify each student in the district-leveldatabase.

Using this individual student-level data on each student, cohort files were builtand course-taking event histories by semester were constructed for each student.With the data constructed in this manner, we calculated our outcome variable: A-Gcompletion. We calculated whether students were A-G eligible or competitively A-Geligible. A-G eligibility is based on a student completing the 15 units in the requiredUC-approved A-G course requirements by the end of 12th grade, of which sevenunits must be taken in the last 2 years of high school. To calculate these outcomemeasures, we need to know which courses were considered "UC-approved courses"and for which requirement they were approved. We learned through conversatiorswith the district, UCOP, and the schools that there are lots of details concerningwhat constitutes a "UC-approved course" for the different A-G requirements. Forexample, if Biology 1A and 1B do not have the 40 hours of lab time required by UCto have it approved as a D requirement, then Biology 1A and 1B can only beapproved as a D requirement if a student has also completed both semesters ofAlgebra IA and IB (or its equivalent) as a prerequisite to Biology 1A. We sought outthe array of details and clarifications by course number in our discussions withUCOP and district staff to make sure that we could include these specific nuancesand differences as part of the code for calculating A-G eligibility.

Empirical Framework

Generally, the impact of participating in an activityin this case the effect ofparticipating in EAOP activitiescannot be measured by comparing the outcomes ofthose who choose to participate in the activity against the outcomes of those who donot participate. There may be characteristics that are related to both choosing toparticipate in the given activity and to the outcomes of interest; this is known as aself-gelection problem. To address this self-selection problem and be able to examinethe impact of participating in EAOP on students' A-G completion, this reportcompares students with a high probability of participation in EAOP to similarstudents at schools that did not offer EAOP. This approach measures the impact ofparticipation because it takes into account the student and school characteristics ofstudents who have similar characteristics to participants in EAOP, but did notparticipate because their schools did not offer it.

To measure the impact of participation, we first estimated the likelihood ofparticipating in EAOP for those individuals at schools offering these activities. Thisestimation identified those characteristics associated with a high probability of

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participation. The procedure and method for predicting participation as well as theresults of this estimation are explained in the next section.

' Next, we identified students at schools not offering EAOP who had similarcharacteristics to those students who participated in EAOP at schools that offered it.Based on the characteristics that we found that predict participation in EAOP (stepone above), we calculated an "out-of-sample" prediction of participation for eachindividual in the schools that do not offer EAOP. This means that based or thecoefficients from the prediction model for the 'student characteristics (theindependent variables in the prediction model, i.e., gender, ethnicity, etc. wecalculate a predicted value of participation in EAOP for the students who are inschools that do not offer EAOP.

As a result, students attending schools who do not offer EAOP have acalculated probability of participation in EAOP. This enabled us to identify students

1111with both a high and a low probability of participation in EAOP at schools that donot offer EAOP. With this information, we could then compare the outcomes ofstudents with a high probability of participation at schools that offer EAOP and theoutcomes of students with a high probability of participation in schools that do notoffer EAOP. This comparison of high probability students, in schools that offerEAOP and schools that do not offer EAOP, measures the impact of participation inEAOP accounting for any self-selection.

One concern remains however with using this comparison to measure theimpact of participation. Other differences may exist that are not observed betweenthe schools offering EAOP and those schools that do not offer EAOP. To address thisissue, we further identified two groups: individuals with a low probability ofparticipation in EAOP at schools offering it and students with a low probability ofparticipation in EAOP at schools that do not offer it.

Identifying these two groups allows us to further compare the outcomes ofstudents with a low probability of participation in schools that do offer EAOP andthe outcomes of students with a low probability of participation in schools that donot offer EAOP. The observed difference in outcomes between the two lowprobability groups then serves as a control for the difference in outcomes acrossstudents in schools that offer EAOP and schools that do not offer it.

Therefore, to identify the program effect, we basically examine the difference inthe differences between high probability individuals and low probability

individuals. (See Meyer, 1995, for a more detailed explanation of difference indifferences methodology).

We generalize this technique and control for other differences between schoolsand students within a regression framework. We are able to control for, the meandifferences in outcomes of students at school that offer and do not offer EAOP, theprobability of participating in EAOP for individuals at both groups of schools, andthe probability of participating in EAOP at schools that offer EAOP. The regressionequation is calculated using pooled data from the two groups of students: those atschools offering EAOP and those at schools not offering EAOP. This approach iscomparable to having a natural experiment.

Yit = ao + dt + d + dt" + I OK z Ill< + Eft (1)

where the outcome yit represents student I in school group t with a score 1 .if thatstudent is UC eligible and 0 otherwise, t is the dummy variable with the value 1 ifthe school is an EAOP school and 0 otherwise, d it is the student's propensity score(or predicted probability of participating in the EAOP program for all students [asdescribed above']), z itK is a vector of other explanatory variables, and Eit is randomerror in yit , with the Eit assumed independent. j = 0 and 1, where j = 1 is the group of

students at a school that offer EAOP and j = 0 is the group of students at schools thatdo not offer EAOP. The interaction term, dt*d it takes the value of the probability

of participation in EAOP when an individual attends a school that offers EAOP andtakes on the value of 0 when an individual attends a school that does not offerEAOP. This interaction term indexes the difference between the relationship of d it to

UC eligibility in schools offering EAOP and schools not offering it, which is anindirect estimate of the difference in Equation 2. We also include, I 8K z itK , which is

an additional vector of explanatory variables as a simple way to adjust forobservable differences between the individuals in the different groups. This controlsfor factors that simultaneously affect participation in EAOP and subsequentcompletion of UC college preparatory coursework.

Moreover, 13 is the effect of participation on the outcome. The key identifyingassumption is that 13 would be 0 in the absence of participation in EAOP; that is,there would be no difference in the mean of those in group 0 and group 1. In thiscase, an unbiased estimate of 13 can be obtained by difference in differences as :

unbiased estimate of (3 = A yo'yoo

= (T711- 1o5 (Y1° S0°) (2)

where a bar indicates an average over I; the subscript denotes whether theindividuals are in a school that offers EAOP; and the superscript denotesparticipation.

Again, 13 can be estimated directly by applying ordinary least squares, or this

case logistic regression, to Equation (1). This method reproduces the estimate iof p,

indicated in Equation (2). The advantage of the regression formulation is that itmakes clear that the key identifying assumption is that there is no interactionbetween being in a school that offers EAOP and participating in EAOP (except forthe influence under study). This approach, as explained above, therefore estimatesthe effect of participation in EAOP by correcting for the self-selection problemwithin a school and correcting for the mean differences among schools that offer anddo not offer EAOP. This method is able to eliminate the most likely type of selectionbias. We correct for the selection bias that is present when a student with a highprobability of participating in EAOP chooses to participate. But we are not able tocorrect for the selection bias that could occur when a student with a high probabilityof participating in EAOP chooses to attend a high school only because the schooloffers EAOP.

Concerned about this potential bias, we investigated the backgroundcharacteristics and traveling program choices of students in EAOP at EAOP schoolsand non-EAOP students at EAOP schools, as well as students at non-EAOP schools.Refer to Appendix A for these tables by students in EAOP at EAOP schools and non-EAOP students at EAOP schools as well as students at non-EAOP schools. We foundthat most students do not have their choice of high school because their high schoolis based on their resident location. We did not find any differences that wouldsuggest that students who either voluntarily choose their high school or who attendtheir neighborhood high school are any more likely to be at an EAOP school; thus,suggesting that students are not choosing high schools based on the presence of theprogram. Additionally, we correct for all mean differences in schools, except for thefact that they offer EAOP. In the end, this method eliminates the largest sources of

endogeneity.

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Lastly, identification of participation in EAOP is possible through the variablesthat were included in the prediction equation that constructed d it, but wereexcluded in the regression equations, Equation (1) that include d it as anindependent variable. The identifying variables for participation in EAOP are:Grade 9 GPA, ethnicity, and whether and with what grade (A, B, C, D, or F) astudent completed both semesters of Algebra I (or its equivalent) by the end of ninthgrade. We used these variables to identify participation in EAOP because generallystudents are selected to be part of the EAOP program if they are "showing promise"at the end of ninth grade. This generally means that a student has a GPA of a 3.0 orabove at the end of ninth grade and has completed both semesters of Algebra I (orits equivalent) by the end of ninth grade. Students are selected based on a review oftheir transcripts at the very beginning of 10th grade. EAOP staff assess the coursestaken and completed by the student as well as their overall ninth-grade GPA. Theyare looking for students that are essentially on-track to completing the A,Grequirements at the end of ninth grade and show a level of academic performancethat warrants completing the UC preparatory coursework. Generally a. student on atraditional path would need to have completed Algebra I (or its equivalent) andEnglish 9 by the end of ninth grade to be considered on track. Furthermore, ethnicityalso is used to identify participation in EAOP. EAOP makes its program supportavailable to all students who express interest. EAOP also works in schools that havenot performed well historically and this correlates highly with schools having alarge percentage of minority students. (See Table 1 for results).

Predicting Participation in EAOP at Schools That Offer It

In our pooled sample of 46,817 students, which includes both cohort years ofdata on ninth graders staring in 1996/'97 and 1995/'96, 7.0% of the individualsparticipated in EAOP. The 3,296 participantsthe 7%participated in a full 3 yearsof the EAOP program in high school during Grades 10, 11, and 12. In addition, 98%of the students who were selected to be in EAOP in ninth grade participate in theprogram for the full 3 years. Nearly three quarters (72.5%) of the study sample wereenrolled at schools that offered EAOP to their students. In our study, out of 101 highschools, EAOP operated at 38; 20 of which have magnet programs at the highschools. Finally, the EAOP program does not necessarily operate every year at everyhigh school, meaning that in some schools in some years, EAOP does not selectstudents to participate in the EAOP program. However, if a student is selected into

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EAOP and starts participating in the 10th grade, then they will be serviced by the

EAOP program and participate in the program for their entire high school career.

Moreover, of those students in schools that offered EAOP, 9.7% participate inEAOP during their sophomore, junior, and senior year. Based on these individualsand their characteristics, we estimated a predictive regression equation for thoseindividuals in schools that offered EAOP based on what factors we understandinfluence a student to participate in EAOP. As noted earlier, traditionally, studentswho have a grade point average above a 3.0 for their ninth grade year and havecompleted Algebra I or its equivalent by the end of ninth grade (i.e., in eighth orninth grade) and English 9 by the end of ninth grade have a greater opportunity toparticipate in EAOP because EAOP aims to select students who have shown"potential" during ninth grade. Moreover, we hypothesize that students of differentraces, gender, language status, and economic background (operationalized by Title 1

status and whether a student qualifies to receive free and reduced lunch) makedifferent choices about what programs to participate in during high school.

Table 1 below presents the results from the predictive regression ofparticipation in EAOP for those students in schools that offer EAOP. The predictedvalue of participation in EAOP from this regression is calculated for each student ina school that offers EAOP. The regression yields the probability of participating inEAOP. Moreover, the coefficients reported in Table 1 were used (in the predictionequation described above) to predict participation in EAOP for those students whoare at schools that do not offer EAOP. Refer to Appendix B for the means andstandard deviations for all the variables in the prediction model for all students,students in EAOP schools, and students in non-EAOP schools.

In general, we found that students who participate in EAOP have the followingindividual characteristics: they are Hispanic and not white, Asian or Filipino; havehigh grade point averages in ninth grade, as well as in Grades 10-12; completeAlgebra I (or its equivalent) by the end of ninth grade with an A, B or C grade;complete English 9 by the end of ninth grade with an A, B, or C grade; have non-limited English proficient status; and are not participating in the free/reduced lunchprogram. These findings suggest that participation in EAOP is dependent on ability,

high school courses or programs, student's ethnicity and language abilities, as well

as their familial economic status.

Table 1

Predictive Estimation of Participation in EAOP for Students in Schools ThatOffer EAOP

Step -2 Log Cox & Snelllikelihood R Square Nagelkerke R Square

2 12852.163 .228 .482

B B S.E. Wald df Sig. Exp(B)

Grade 9 GPA 1.231 .067 342.288 1 .000 3.426

Grade 10-12 A-F GPA 1.391 .045 965.884 1 .000 4.020

Algebra 1 217.476 4 .000

Left cohort 1.403 1.740 .650 1 .420 4.067

Complete 'D or F' .158 .090 3.055 1 .080 1.171

Complete 'C' .840 .068 152.426 1 .000 2.317

Complete 'A or B' .792 .065 150.171 1 .000 2.207

English 9 (A or B) 91.798 3 .000

Complete 'D or F' .075 .151 .251 1 .617 1.078

Complete 'C' .714 .110 42.143 1 .000 2.042

Complete 'A or B' .806 .100 64.619 1 .000 2.240

Ethnicity 773.148 6 .000

American Indian .600 .359 2.796 1 .094 1.821

Asian -2.315 .106 477.545 1 .000 .099

Black -.114 .089 1.638 1 .201 .892

White -1.822 .087 436.588 1 .000 .162

Filipino -1.461 .125 136.956 1 .000 .232

Pacific-Islander -.997 .434 5.287 1 .021 .369

Female .015 .047 .100 1 .752 1.015

Non-LEP .514 .083 38.430 1 .000 1.671

Free Lunch 106.759 2 .000

Non-Part -.617 .061 103.695 1 .000 .540

Missing -.496 .148 11.311 1 .001 .609

Not Title 1 -.064 .053 1.453 1 .228 .938

Constant -10.439 .217 2318.802 1 .000 .000

Note: Reference groups are Hispanic, Male, LEP, Free/Reduced Lunch, ReceivingTitle 1.

60 0

16

IV. Results

Our analyses provide information on the A-G completion of high schoolseniors. Most importantly, our results inform us about the impact of participation inEAOP on the outcome measure of A-G eligibility. Table 2 reports the outcomemeasure, A-G eligibility by EAOP status. Appendix A reports the backgroundcharacteristics of students who participated and did not participate in EAOP inschools that offer EAOP as well as for students not in an EAOP school. Table 3reports the simple logistic regression results of EAOP status on A-G eligibility statusfor only students in EAOP schools indicating the estimated likelihood of A-Gcompletion for EAOP students compared to non-EAOP students in EAOP schools.Finally, Table 4 reports the logistic regression results for Equation (2) that includethe estimated program effect, which is estimated using the interaction term(PRED*School Interaction). More general implications are discused in theconclusion section.

Impact of Participating in EAOP

Basically, with a simple comparison we found that 40.0% of EAOP students areA-G eligible by the end of 12th grade, whereas only 9.5% of non-EAOP students areA-G eligible by the end of 12th grade (see Table 2). We also found by a simple logisticregression of EAOP on A-G eligibility, that EAOP students are twice as likely toachieve A-G eligibility by the end of 12th grade (see Table 3). These results motivatethe further investigation of the impact of EAOP, but are not conclusive about theimpact of EAOP for reasons of self-selection and endogeneity (as stated above). Thusto formally test the hypothesis that the academic development services offered bythe University of California via EAOP result in more students completing the UCpreparatory coursework, the first hurdle to being eligible for applying and beingadmitted to the University of California, we need to estimate Equation (2) asexplained in the Empirical Framework section.

Table 2

Grade 9 Fall '95-'96 and '96-'97 Pooled Cohort (Students With 'Complete' Data)Final Eligibility and EAOP Status

EAOP Status

Non-EAOP EAOPStudent Student Total

Not A-F eligible

Count% within column

A-F eligible


Total


39404 1973 41377

90.5% 59.9% 88.4%

4117 1323 5440

9.5% 40.1% 11.6%

43521 3296 46817

100.0% 100.0% 100.0%

Table 3

Estimated Likelihood of A-G Eligibility for Students Who Participated in EAOP asCompared to Students Who Did Not Participate in EAOP in Schools That Offer EAOP

(N = 33,965) Coefficient Standard Error Wald

EAOP 2.236 0.042 2800.291

Estimating Equation (2), as explained above, controls for self-selection. andendogeneity. The results of this pooled estimation, found in Table 4, suggest thatthere is a definitive impact of EAOP participation on the A-G completion of highschool seniors. The clearest method of interpreting this model is to investigate thecoefficient of the interaction term. As shown in Table 4, the coefficient of theinteraction term is a log odds of +0.763, which equals an odds ratio of 2.1447 (e °.763 =

2.1447). Therefore, the model tells us that if a student is a participant in EAOP theyare twice (2.14) as likely to complete the UC college preparatory coursework by the

end of 12th grade than students who do not participate in EAOP.

Specifically, Table 4 reports the results of the pooled logistic regression thatincludes a school dummy variable (EAOP School), indicating whether the schooloffered EAOP, and a predicted participation variable (EAOP Prediction) for allstudents, regardless of whether the school offers EAOP were included to measurethe comparability of the groups; and a school/participation interaction term

18 22

(PRED*School Interaction), indicating the probability of participating in EAOP forthose individuals at schools that offer EAOP and 0 for those individuals not at aschool that offers EAOP. Additional independent variables also were included tocontrol for student and school factors that simultaneously affect participation andsubsequent A-G completion. The overall fit of the model is judged by theNagelkerke measure (or the Cox & Snell measure) (Kennedy, 1992). The corollary forthese measures in ordinary least squares (OLS) regression is the W statistic. Thegoodness of fit that the Nagelkerke or Cox & Snell measure reflects is between twomodels examined in a Likelihood Ratio test and not between a model and observeddata as is the case with linear regression. The value falls between 0 and 1 and tendsto be much lower than the R2 statistic in linear regression analysis (Steinberg &Co lla, 1991). A low number does not necessarily imply a poor fit, and valuesbetween 0.20 and 0.40 are considered very satisfactory. On this basis, our modelsappear satisfactory.

The interpretation of a positive coefficient on the school/participationinteraction term (PRED*School Interaction) is that individuals who participate inEAOP during their high school years are more likely to complete the A-G course

1111

requirements by the end of 12th grade controlling for the choice of participation andthe school differences related to offering EAOP. In addition, a negative coefficientindicates "less likely to complete." Moreover, the interpretation of the coefficient ofthe interaction term, which is a log odds of +0.763 and can be transformed into anodds ratio of 2.1447 (e.' = 2.1447), is that if a student is a participant in EAOP theyare twice (2.14) as likely to complete the UC college preparatory coursework by the

end of 12th grade than students who do not participate in EAOP.

To further investigate the program effect of EAOP, we replicated our analysesof modeling the prediction of EAOP and estimating the impact of EAOP withEquation (2) for each of the cohort years separately - 1995/'96 and 1996/'97 cohorts.This yielded the same result. In both years the interaction term was significant at the.01 level and positive. The program effect was slightly stronger in 1995/'96: in1995/'96, the analysis yielded a Wald of 8.46 on the interaction term with aNagelkerke R Squared of .598, as compared to a Wald of 6.71 with a Nagelkerke R

Squared of .628 in 1996/'97.

Furthermore, we decided to also replicate our analyses of predicting EAOP andEquation (2) using a restricted population. We selected out of the full populationonly students who had a 3.0 grade point average at the end of ninth grade and had

completed Algebra I or its equivalent with any grade by the end of ninth grade. Thisallowed us to investigate the effect of EAOP on students who have done very well inninth grade and are considered on-track toward A-G completion at the end of ninthgrade. This restriction reduced our pooled population down to 10,251 students ascompared to the full population of 46,817. This also reduced our EAOP studentgroup down to 2,273 as compared to the 3,296 in the full population. We conductedour pooled analyses as well as separate year analyses using the restrictedpopulation. The only difference in the modeling was that with the restricted

olpopulation we had fewer categories on the Algebra I and English 9 completi nvariables. The restriction on the population eliminated three categories: "left thecohort," "did not complete Algebra I by end of ninth grade," and "did not completeEnglish 9 by the end of Grade 9." Again, we found a positive and even strongerprogram effect for EAOP participation. The models for the pooled analysis using therestricted population yield a Wald of 20.92 on the interaction term with aNagelkerke R Squared of .439.

In sum, we found in the pooled analysis, the separate cohort analysis for thefull population, as well as these analyses for the restricted population that thecoefficient for the interaction term was significant and positive. Specifically, thecoefficient of the interaction term (a log odds of +0.763) equals an odds ratio of2.1447 (e"' = 2.1447). The model tells us that students who participate in EAOP aretwice (2.14) as likely to complete the UC college preparatory coursework by the endof 12th grade than students who do not participate in EAOP, indicating that EAOPhas a large, positive effect on an individual's completion of UC coursework duringhigh school.

1

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I

I

I

I

I

I

I

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Table 4

Estimated Impact of EAOP Participation on A-G Eligibility Controlling for StudentCharacteristics, Student Selection, and EAOP School Status

Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square

10 15863.999 .317 .615

B B S.E. Wald df Sig. Exp (B)

EAOP Prediction -1.106 .182 37.012 1 .000 .331

EAOP School -.548 .066 68.570 1 .000 .578

PRED*School Interaction .763 .187 16.616 1 .000 2.145

A-F GPA (Grade 10-12) 2.930 .051 3273.251 1 .000 18.73

English 9 740.308 4 .000

Left cohort 2.470 1.613 2.345 1 .126 11.821

Complete 'D or F' -.264 .197 1.799 1 .180 :768

Complete 'C' 2.095 .121 300.057 1 .000 8.122

Complete 'A or B' 2.514 .115 481.971 1 .000 12.351

Female -.310 .042 54.307 1 .000 .734

Non-LEP .442 .087 26.017 1 .000 1.556

Free lunch 9.362 2 .009

Non-part .013 .052 .061 1 .805 1.013

Missing -.405 .139 8.555 1 .003 .667

Not Title 1 .004 .055 .005 1 .942 1.004

1996-'97 cohort .623 .042 224.479 1 .000 1.865

Constant -12.314 .195 4003.918 1 .000 .000

Note: Reference groups are Hispanic, Male, LEP, Free/Reduced Lunch, and Receiving Title 1.

V. Conclusion

Overall, we found in a simple comparison that in schools that offer EAOP,more students who participated in EAOP completed the UC A-G preparatory course

requirements by the end of 12th grade as compared to students who do notparticipate in EAOP. This simple comparison, however, did not take into accountcharacteristics that are related to both choosing to participate in the EAOP programand to the outcome of interest. This is known as a self-selection problem. Controllingfor self-selection, we find compelling evidence of higher completion of A-G courses

by the end of 12th grade by participants of EAOP than by non-participants of EAOP.

We find that students who participate in EAOP are twice (2.14) as likely to completethe UC college preparatory coursework by the end of 12th grade than students who

21 25

do not participate in EAOP. This suggests that there is a large, positive independentimpact from participation in EAOP and that the observed effect is not driven byselection. Our results are compelling because we found the same results acrosspoOled analyses and separate cohort analyses for the full population of students inthe given district as well as across pooled analyses and separate cohort analyses fora restricted population of just those students who were on-track at the end of ninthgrade. In sum, our results suggest that students who participate in EAOPthroughout high school are twice as likely to complete the UC preparatorycoursework by the end of 12th grade than are non-participants of EAOP.

2 6

22

I

References

Kennedy, P. (1992). A Guide to Econometrics (3rd ed.). Cambridge, MA: The MIT Press.

Meyer, B. D. (1995). Natural and Quasi-Experiments in Economics. Journal of Businessand Economics Statistics, 13, 151-161.

Steinberg, D., & Co lla, P. (1991). LOGIT: A Supplementary Module for SYSTAT.Evanston, IL: SYSTAT Inc.

Appendix A:Student Characteristics by Students in EAOP at EAOP Schools and Non-EAOP

Students at EAOP Schools as Well as Students at Non-EAOP Schools

2824

Table A.1

Grade 9 Fall 95-96 and 96-97 Pooled Cohort (Students With 'Complete' Data) FinalEligibility and EAOP School and Student Status

EAOP School

Non-EAOPSchool

Non-EAOPStudent

EAOPStudent Total

Not A-F eligible

Count 10786 28618 1973 41377

% within column 83.9% 93.3% 59.9% 88.4%

A-F eligible

Count 2066 2051 1323 5440

% within column 16.1% 6.7% 40.1% 11.6%

Total

Count 12852 30669 3296 46817

% within column 100.0% 100.0% 100.0% 100.0%

Table A.2

Grade 9 Fall '95-'96 and '96-'97 Pooled Cohort (Students With 'Complete' Data) Algebra 1 byNinth Grade Benchmark by EAOP Program Participation

Non-EAOPSchool

EAOP School

Non-EAOPStudent

EAOPStudent Total

Left District(s) in ninth

Count 1 9 1 11

% within column .0% .0% .0% .0%

Incomplete or no courses

Count 5428 16047 563 22038

"Yo within column 42.2% 52.3% 17.1% 47.1%

Completed with < 'C'


Completed with 'C'

2467

19.2%

6620

21.6%

227

6.9%

9314

19.9%

Count 2297 4208 767 7272

% within column 17.9% 13.7% 23.3% 15.5%

Completedwith 'A or B'

Count 2659 3785 1738 8182

% within column 20.7% 12.3% 52.7% 17.5%

Total

Count 12852 30669 3296 46817

% within column 100.0% 100.0% 100.0% 100.0%

2630

Table A.3

Grade 9 Fall '95-'96 and '96-'97 Pooled Cohort (Students with 'Complete' Data) English 9 byNinth Grade Benchmark by EAOP Program Participation

Non-EAOPSchool

EAOP School

TotalNon-EAOP

StudentEAOP

Student

Left District(s) in ninth

Count 1 9 1 11

% within Column .0% .0°/0 .00/0 .0%

Incomplete or no courses

Count 1825 5784 229 7838

within Column 14.2% 18.9% 6.9% 16.7%

Completed with < 'C'

Count% within Column

Completed with 'C'

327125.5%

970331.6%

932.8%

1306727.9%

Count 3271 9703 93 13067

% within Column 25.5% 31.6% 2.8% 27.9%

Completedwith 'A or B'

Count 4612 7531 2455 14598

% within Column 35.9% 24.6% 74.5% 31.2%

Total

Count 12852 30669 3296 46817

% within Column 100.0% 100.0% 100.0% 100.0%

Table A.4

Grade 9 Fall '95-'96 and '96-'97 Pooled Cohort (Students with 'Complete' Data)

Ethnicity by EAOP Program Participation

Non-EAOPSchool

EAOP School

TotalNon-EAOP

StudentEAOP

Student

American Indian

Count 55 79 15 149

% within column .4% .30/0 .50/0 .3%

Asian

Count 1404 1428 167 2999

% within column 10.9% 4.7% 5.1% 6.4%

Black


Hispanic


White

Count

128010.0%

666151.8%

3017

337111.0%

21622.70.5%

3204

2397.3%

244374.1%

305

489010.4%

3072665.6%

6526

% within column 23.5% 10.4% 9.3% 13.9%

Filipino

Count 393 843 119 1355

% within column 3.1% 2.7% 3.6% 2.9%

Pacific Islander

Count 42 122 8 172

% within column.30/0 .4% .2% .4%

Total

Count 12852 30669 3296 46817

% within column 100.0% 100.0% 100.0% 100.0%

28

Table A.5

Grade 9 Fall '95-'96 and '96-'97 Pooled Cohort (Students With 'Complete' Data)Gender by EAOP Program Participation

Non-EAOPSchool

'EAOP School

TotalNon-EAOP

StudentEAOP

Student

Male

Count % within 6334 15607 1233 23174column 49.3% 50.9% 37.4% 49.5%

Female


Total


Table A.6Grade 9 Fall '95-'96 and '96-'97 Pooled Cohort (Students With 'Complete'Data) LEP Status Fall grade 10 by EAOP Program Participation

EAOP School

Non-EAOP Non-EAOP EAOPSchool Student Student Total

LEP 2365 8868 340 11573

Count % within 18.4% 28.9% 10.3% 24.7%column

Non-LEP 10487 21801 2956 35244


Total 12852 30669 3296 46817


3329

Table A.7

Grade 9 Fall '95-'96 and '96-'97 Pooled Cohort (Students With 'Complete'Data) Meal Program Fall Grade 10 by EAOP Program Participation

EAOP School


Non-partic/Full pay

Count % withincolumn

Free/Reduced

6293 9733 794 16820

49.0% 31.7% 24.1% 35.9%

I

a

Count % withincolumn

6159

47.9%

19667

64.1%

2427

73.6%

28253

60.3%a

Missing


Total ICount % within 12852 30669 3296 46817column 100.0% 100.0% 100.0% 100.0%

Table A.8Grade 9 Fall '95-'96 and '96-'97 Pooled Cohort (Students With 'Complete' Data)Title 1 Fall Grade 10 by EAOP Program Participation

EAOP School


Not Title 1

Count % within 10585 17579 2180 30344

column 82.4% 57.3% 66.1% 64.8%

Title 1

Count % within 2267 13090 1116 16473

column 17.6% 42.7% 33.9% 35.2%

Total

Count % within 12852 30669 3296 46817

column 100.0% 100.0% 100.0% 100.0%

a

a

a

Table A.9

Grade 9 Fall '95-'96 and '96-'97 Pooled Cohort (Students With 'Complete' Data)Travel Program Fall Grade 10 by EAOP Program Participation

Non-EAOPSchool

EAOP School

TotalNon-EAOP

StudentEAOP

Student

Not in travel prog

Count °/0 withincolumn

Involuntary

Count % within

888869.2%

838

2714288.5%

543

268481.4%

33

3871482.7%

1414

column 6.50/o 1.80/0 1.0°/0 3.0°/0

Voluntary

Count % within 3126 2984 579 6689

column 24.3% 9.7% 17.6% 14.8°/0

Total

Count % within 12852 30669 3296 46817

column 100.0% 100.0% 100.0% 100.0%

Table A.10Grade 9 Fall '95-'96 and '96-'97 Pooled Cohort (Students With 'Complete' Data)Mean GPA by Grade and EAOP Program Participation

Non-EAOPSchool

EAOP School

TotalNon-EAOP

StudentEAOP

Student

Grade 9Mean 2.54 2.32 3.38 2.46N 12791 30567 3294 46652

Grade 10-12Weighted AP

MeanN

2.2512733

1.9530331

3.213296

2.1246360

31 35

Appendix B:Means & Standard Deviations for Variables Included in the

'Predictive Estimation of Participation in EAOP for Students in SchoolsThat Offer EAOP' Presented in Table 1 for All Students, Students in

EAOP Schools, and Students in Non-EAOP Schools

32 36

Table B.1EAOP Variable Descriptives: All Students for the Pooled Data in Both EAOP andNon-EAOP Schools

Variable N Min. Max. Mean or % SD

Grade 9 GPA 46652 0.0 4.0 2.457 0.841

Grade 10-12 A-F GPA 46360 0.0 4.9 2.123 0.934

Algebra 1

Left cohort 46817 0.0 1.0 0.000 0.015

Did not complete 46817 0.0 1.0 ' 0.471 0.499

Complete 'D or F' 46817 0.0 1.0 0.199 0.399

Complete 'C' 46817 0.0 1.0 0.155 0.362

Complete 'A or B' 46817 0.0 1.0 0.175 0.380

English 9 (A or B)

Did not complete 46817 0.0 1.0 0.167 0.373

Complete 'D or F' 46817 0.0 1.0 0.279 0.449

Complete 'C' 46817 0.0 1.0 0.241 0.428

Complete 'A or B' 46817 0.0 1.0 0.312 0.463

Ethnicity

American Indian 46817 0.0 1.0 0.003 0.056

Asian 46817 0.0 1.0 0.064 0.245

Black 46817 0.0 1.0 0.104 0.306

Hispanic 46817 0.0 1.0 0.656 0.475

White 46817 0.0 1.0 0.139 0.346

Filipino 46817 0.0 1.0 0.029 0.168

Pacific Islander 46817 0.0 1.0 0.004 0.061

Female 46817 0.0 1.0 0.505 0.500

Non-LEP 46817 0.0 1.0 0.753 0.431

Free Lunch

Non-Part 46817 0.0 1.0 0.359 0.480

Missing 46817 0.0 1.0 0.037 0.189

Not Title 1 46817 0.0 1.0 0.648 0.478

33 3 7

Table B.2EAOP Variable Descriptives: Pooled Data for Students in EAOP Schools Only

Variable N Min. Max. Mean or % SD

Grade 9 GPA 33861 0.0 4.0 2.425 0.843

Grade 10-12 A-F GPA 33627 0.0 4.9 2.076 0.931

Algebra 1

Left cohort 33965 0.0 1.0 0.000 0.017

Did not complete 33965 0.0 1.0 0.489 0.500

Complete 'D or F' 33965 0.0 1.0 0.202 0.401

Complete 'C' 33965 0.0 1.0 0.146 0.354

Complete 'A or B' 33965 0.0 1.0 0.163 0.369

English 9 (A or B)

Did not complete 33965 0.0 1.0 0.177 0.382

Complete 'D or F' 33965 0.0 1.0 0.288 0.453

Complete 'C' 33965 0.0 1.0 0.240 0.427

Complete 'A or B' 33965 0.0 1.0 0.294 0.456

Ethnicity

American Indian 33965 0.0 1.0 0.003 0.053

Asian 33965 0.0 1.0 0.047 0.212

Black 33965 0.0 1.0 0.106 0.308

Hispanic 33965 0.0 1.0 0.709 0.454

White 33965 0.0 1.0 0.103 0.304

Filipino 33965 0.0 1.0 0.028 0.166


Female 33965 0.0 1.0 0.504 0.500

Non-LEP 33965 0.0 1.0 0.729 0.445

Free Lunch

Non-Part 33965 0.0 1.0 0.310 0.462

Missing 33965 0.0 1.0 0.040 0.195

Not Title 1 33965 0.0 1.0 0.582 0.493

3834

Table B.3EAOP Variable Descriptives: Pooled Data for Students in Non-EAOP Schools Only

Variable N Min Max. Mean or % SD

Grade 9 GPA 12791 0.0 4.0 2.539 0J333

Grade 10-12 A-F GPA 12733 0.0 4.7 2.250 0.931

Algebra 1

Left cohort 12852 0.0 1.0 0.000 0.009

Did not complete 12852 0.0 1.0 0.422 0.494

Complete 'D or F' 12852 0.0 1.0 0.192 0.394

Complete 'C' 12852 0.0 1.0 0.179 0.383

Complete 'A or B' 12852 0.0 1.0 0.207 0.405

English 9 (A or B)

Did not complete 12852 0.0 1.0 0.142 0.349

Complete 'D or F' 12852 0.0 1.0 0.255 0.436'

Complete 'C' 12852 0.0 1.0 0.245 0.430

Complete 'A or B' 12852 0.0 1.0 0.359 0.480

Ethnicity

American Indian 12852 0.0 1.0 0.004 0.065

Asian 12852 0.0 1.0 0.109 0.312

Black 12852 0.0 1.0 0.100 0.299

Hispanic 12852 0.0 1.0 0.518 0.500

White 12852 0.0 1.0 0.235 0.424

Filipino 12852 0.0 1.0 0.031 0.172


Female 12852 0.0 1.0 0.507 0.500

Non-LEP 12852 0.0 1.0 0.816 0.388

Free Lunch

Non-Part 12852 0.0 1.0 0.490 0.500

Missing 12852 0.0 1.0 0.031 0.174

Not Title 1 12852 0.0 1.0 0.824 0.381

Endnotes

dt, is a constructed variable with a predicted value for participation in EAOP for those students in

schools that offer EAOP and with the calculated out-of-sample predicted value for those students in schools

that do not offer EAOP. The predicted value and the calculated out-of-sample predicted value are both based

on the regression results in Table 1. In a natural experiment, dit would be a dummy for participation in) EAOP

for both groups, but that is not possible in this case.

40

36

tifil ,

1, , .1,, 'fi,,';,, i 3 , , i : ' ' , - '

,i, .. Y + ' I s'''. ; '1.'IL1...2,4,44.101,,,2,'

;r it: tit,

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DOCUMENT RESUME Quigley, Denise D. TITLEDOCUMENT RESUME ED 475 140 TM 034 827 AUTHOR Quigley, Denise D. TITLE The Early Academic Outreach Program (EAOP) and Its Impact on. High School